Searching for emergent representations in evolved dynamical systems

Thomas Hope, Ivilin Stoianov, Marco Zorzi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper reports an experiment in which artificial foraging agents with dynamic, recurrent neural network architectures, are "evolved" within a simulated ecosystem. The resultant agents can compare different food values to "go for more," and display similar comparison performance to that found in biological subjects. We propose and apply a novel methodology for analysing these networks, seeking to recover their quantity representations within an Approximationist framework. We focus on Localist representation, seeking to interpret single units as conveying representative information through their average activities. One unit is identified that passes our "representation test", representing quantity by inverse accumulation.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages522-533
Number of pages12
Volume4095 LNAI
ISBN (Print)3540386084, 9783540386087
Publication statusPublished - 2006
Event9th International Conference on Simulation of Adaptive Behavior, SAB 2006 - Rome, Italy
Duration: Sep 25 2006Sep 29 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4095 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other9th International Conference on Simulation of Adaptive Behavior, SAB 2006
CountryItaly
CityRome
Period9/25/069/29/06

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Hope, T., Stoianov, I., & Zorzi, M. (2006). Searching for emergent representations in evolved dynamical systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4095 LNAI, pp. 522-533). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4095 LNAI). Springer Verlag.